When Nara announced its existence to the world at the time of a June 2012 Series A round, it made some pretty enormous promises. The company aimed to reinvent search through the use of machine learning and promised to “organize and personalize the Web just for you.” Boasting a team of “neuroscientists, creative artists, computer scientists, astrophysicists and technology and Internet industry veterans,” Nara explained its mission as to create a “Web-scale recommendation engine powered by a brain-like architecture.”

Pretty heady stuff.

The company started slow, initially mapping only restaurants, and further still, only those in eight cities. But it quickly expanded to 25 then 50 cities, and then ultimately nationwide. The promise was that the system could learn about your tastes from what restaurants and dishes you liked in your hometown, and then make more personalized recommendations when you were in a new location.

And learn it did. Nara’s recommendations were fairly accurate in my experience, and revealed some hidden gems that Yelp, Foursquare, and Google seemed to miss. But still, the service available at Nara.me and through the company’s accompanying mobile app seemed to be offering just a glimpse at its full power.

Today, that glimpse gets a little larger, as Nara is expanding its offering to hotel search. Hotels are more of a evolutionary than a revolutionary step forward, but it shows Nara’s ability to extend its mapping to additional consumer categories, and paves the way for the addition of recommendations for shopping, entertainment, content, and a variety of topic areas.

Like in the restaurants category, where Nara partnered with OpenTable, the company is entering the hotels category in partnership with Expedia and TripAdvisor. The travel industry giants will provide the consumer review data that underlies its recommendations engine, and then offer in app booking options once a recommendation has been made.

Users can filter their search by neighborhood, amenities, price, star rating, and other criteria. As results are delivered, the user can thumbs up or thumbs down each recommendation – similar to StumbleUpon – thereby injecting more taste data into the Nara system, which will be used to better personalize future search results.

Initially Nara will be limited to 50 cities across the US and Canada, but will quickly expand to offer nationwide coverage, according to the company’s founder and CEO, Thomas Copeman. Hotel recommendations are also limited to the Nara.me Web platform, and will be coming to a future mobile app update.

The reason for the slow category expansion is that it takes a significant amount of time to map each topic area and to form the data layer from which Nara makes its recommendations. The company is also taking its time to perfect the user experience and learn as much as possible about its current users’ tastes in order to make better recommendations. Nara calls this our Digital DNA and aims to apply it across categories going forward.

“Given the complexity and depth of the data analysis we’re doing, I feel like we’re moving at record speed,” Copeman says. “We’re analyzing and indexing big data at the scale of the Web.”

On a macro level, Nara’s founders have promised the ability to compare and recommend entire neighborhoods. Live in Williamsburg, Brooklyn and planning a trip to Portland, Atlanta, or Rome? Nara may eventually tell you exactly where in each town to hang out, where to shop, where to eat, and where to sleep. This may be a few years off still, but we’re getting a clearer picture today of how that may look.

“From its inception, Nara.me was built to be a 21st century personal Internet portal,” Copeman said in a statement today. “Our initial foray into restaurants and, now, hotels is just the beginning of Nara’s capabilities. We are excited to bring the next generation of search to the hospitality, travel, and leisure markets.”

Part of the challenge facing the company in this early stage has been consumer education. Nara is unlike any other search product on the market, but it’s not immediately clear how so and why that benefits the users. One of the more interesting aspects of Nara’s recommendations is the “Why?” section. The platform attempts to explain each recommendation, including what taste data and what reference restaurants and hotels were used to arrive at a particular search result.

“We feel like we finally saw the light come on in terms of people understanding how is this different than Yelp, UrbanSpoon, TripAdvisor, and other discovery platforms,” Copeman says.

Since April of this year, Nara has offered social component, allowing users to follow friends on the platform. Users also have the option to connect their Facebook profiles to discover and invite friends to platform, but this is not mandatory for using Nara.

Nara raised a total of $7 million in its two-phase Series A round. But, with a 23 person team consisting almost entirely of senior scientists and engineers, this money won’t last forever.

The company hasn’t been slow to monetize, however, entering into revenue sharing agreements with both OpenTable and Expedia around the bookings made through its platform. The company also recently licensed its technology to Asian telecom giant, SingTel, who will launch a white-labeled version of Nara.me to its 450 million subscribers across Asia, beginning in September.

According to Nara’s CEO, this latest relationship is a highly lucrative one, which he described saying, “It’s allowing us to monetize at a very significant level. Overall, we’re in a very good spot financially.”

Nara is creeping up slowly on its promise to personalize the Web. Travel and leisure may not be an everyday necessity for some consumers, but it represents a natural place for the company to start. That said, it’s not the only area in which Nara views the Web differently than Google.

“Travel is very much an a jumping off point for us,” Copeman says. “Our goal is to build a ubiquitous consumer platform for the Web 3.0 world.”

Nara has plenty of work left to do to educate the public as to why personalized Web search is superior to the one-size-fits-all offerings of Google, Bing, and vertical-specific portals like Yelp, UrbanSpoon, and Hotels.com. But, the more categories it adds to its platform and the more it learns about each of its users, the more obvious its value becomes.

Michael Carney is a West Coast Editor at PandoDaily, covering venture capital, financial technologies, ecommerce, on-demand services, and the future of television, among other subjects. He has spent his career exploring the world of early stage technology as an entrepreneur and early-stage investor, working in multiple countries within North and South America and Asia. He is an enthusiast of all things shiny and electronic and is inspired by those who build businesses and regularly tackle difficult problems. You can follow Michael on Twitter @mcarney.

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